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Data Analysis with R

You're reading from  Data Analysis with R

Product type Book
Published in Dec 2015
Publisher
ISBN-13 9781785288142
Pages 388 pages
Edition 1st Edition
Languages
Toc

Table of Contents (20) Chapters close

Data Analysis with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. RefresheR 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data to Reason About the World 6. Testing Hypotheses 7. Bayesian Methods 8. Predicting Continuous Variables 9. Predicting Categorical Variables 10. Sources of Data 11. Dealing with Messy Data 12. Dealing with Large Data 13. Reproducibility and Best Practices Index

Relationships between a categorical and a continuous variable


Describing the relationship between categorical and continuous variables is perhaps the most familiar of the three broad categories.

When I was in the fifth grade, my class had to participate in an area-wide science fair. We were to devise our own experiment, perform it, and then present it. For some reason, in my experiment I chose to water some lentil sprouts with tap water and some with alcohol to see if they grew differently.

When I measured the heights and compared the measurements of the teetotaller lentils versus the drunken lentils, I was pointing out a relationship between a categorical variable (alcohol/no-alcohol) and a continuous variable (heights of the seedlings).

Note

Note that I wasn't trying to make a broader statement about how alcohol affects plant growth. In the grade-school experiment, I was just summarizing the differences in the heights of those plants—the ones that were in the experiment. In order to make statements...

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